\documentclass[a4paper,10pt]{article}
\usepackage{graphicx}
\usepackage{url}
\usepackage[latin1]{inputenc}

% ---- mise en page
	% ---- format de page A4
	\setlength{\textwidth }{16cm}	% largeur de ligne
	\setlength{\textheight}{23cm}   % hauteur du texte
	\setlength{\oddsidemargin}{0cm} % marge pages impaires
	\setlength{\evensidemargin}{0cm}% marge pages paires
	\setlength{\topmargin}{0cm} 	
	\setlength{\headheight}{14pt} 
	\setlength{\headsep}{0.5cm} 

\newcommand{\ff}[1]{ \begin{large}\textbf{#1}\end{large} }
\newcommand{\todo}[1]{ \begin{large}\textbf{#1}\end{large} }

%opening
\title{MyCorporisFabrica~: a Unified Ontological, Geometrical and Mechanical View of Human Anatomy}
\author{Oliver Palombi, Guillaume Bousquet, David Jospin, Fran\c{c}ois Faure}
\date{July 2009}

\begin{document}

\maketitle

\begin{abstract} 
A new anatomical database, My Corporis Fabrica (myCF), is presented. It extends FMA to provide geometrical and mechanical data necessary to build patient-specific mechanical models.
Ontology modeling principles of FMA have been used in myCF to ensure consistency of the representation. Geometrical models are associated to anatomical entities, allowing 3D navigation in anatomical models.
Mechanical parameters (stiffness, density...) and functional informations (stability, motion, mobility...) have been added. The most important contribution of myCF is to link canonical anatomical knowledge to patient-specif data. MyCF adds mechanical parameters to the segmented anatomical entities (medical imaging segmentation) and adds non-visible anatomical entities (as ligaments or fascia) to the generated models. The demonstration is made on the knee joint.
The database design of MyCF makes it open and easily extensible.
\end{abstract}

\section{Introduction}
Anatomical models of the human body are used in an increasing number of domains, ranging from anatomy teaching to statistical studies or physical simulation, and including media applications and telepresence as well as virtual prototyping of cloth. 
Models are often built from scratch according to the specific needs of the target application.
This increases the cost of development and the risk of modeling errors.
Therefore, the need for a comprehensive anatomical database of the human body is rapidly growing.
This database should provide high-level information such as ontological relations, as well as geometrical data for graphics applications or physical parameters for simulations.
It should be incremental, so that new anatomical entities can be added along with the development of the knowledge of the human body.
Moreover, it should be easily extensible so that additional anatomical types of parameters can be set for new applications.
First of all, it should be scientifically correct, so that specialists in various domains can safely invest time and energy in its construction.
Finally, we believe that it should be free and open, so that it becomes a common good which benefits to the whole humanity.

In this paper we present MyCorporisFabrica, an attempt to reach the goals mentioned above.
It is largely based on \ff{inspired by ?} Foundational Model of Anatomy (FMA) \cite{Rosse1998}, an anatomical ontology which can be presented as the most elaborated computer-based knowledge source of anatomy.
Nevertheless, FMA does not include the data necessary to create geometrical or mechanical models of anatomy. My Corporis Fabrica (myCF) extends FMA to provide this additional data.
Additionally, it is based on a novel database structure which considerably eases the extensibility.

The remainder of this paper is organized as follows. In section~\ref{sec:pw}, we rapidly review previous work in the domain. The design of the MyCorporisFabrica database is presented in section~\ref{sec:design}. Applications are discussed in section~\ref{sec:applications}, and concluding remarks are presented in section~\ref{sec:conclusion}.


\section{Previous work} \label{sec:pw}
\todo{Cieter le travail de: 
1) N. Magnenat-Thalmann, J. Schmid, H. Delingette, J. A. Iglesias Guitian and M. Agus. 3D Anatomical Modelling and Simulation Concepts. Eurogrpahics 2009, Tutorial Notes, Munich, Germany, April 2009.}
\todo{Citer les ontologies, ne pas oublier le travail des Thalmann : A generalized approach towards functional modeling of human articulations dans le projet CO-ME www.miralab.unige.ch, et aussi a: http://3dah.miralab.unige.ch/ }
\todo{Veiller à citer le travail des membres du comité de programme}
\todo{http://www.vph-noe.eu/, physiome http://www.physiome.org.nz/ et europhysiome http://www.europhysiome.org/ ....}

\section{Database design} \label{sec:design}
\subsection{Generic concepts}
Entities, Attributes, Relations. Infinite extensibility. 
\ff{Mettre ici la description de la partie théorique de la base. Expliquer que c'est les mêmes concepts que FMA mais organisés pour favoriser l'extensibilité (discuter un exemple simple), et permettre à chacun de contribuer facilement}

\subsection{Instances}
Geometry is one of the most challenging issues in anatomy modeling.
Each anatomical entity can be represented using various types of geometric models (volumetric images, surface or volume meshes, analytical surfaces, implicit surfaces, etc.) at various resolutions or levels of detail.
Consequently, we can not store one single geometrical description for each anatomical entity. 
We instead store, for each entity, a set of instances referenced by file names.
We set no limitation on the file format and the type of geometric models. 
We have developed plugins for Blender~\cite{blender}, a free and open-source geometric modeler, to edit geometrical models of MyCorporisFabrica.
It handles surface meshes and can be used to modify shapes, to displace and resize objects and to label areas such as ligament attachment places. \ff{mettre une figure}

Geometry is often modeled based on medical images which represent several anatomical entities, which can be consistently viewed or simulated together.
We therefore gather the anatomical entities modeled from a given set of medical images in \textit{acquisitions}, which allows us to retrieve all of them simultaneously form the database.
\ff{Décrire la partie instances et acquisitions de la base de donnés}

\section{Implementation}
MyCorporisFabrica is available as ....

Interface tools....(images)


\section{Applications} \label{sec:applications}
Gathering ontological, geometrical and mechanical data consistently in a database allows new applications. We sketch some of them in this section.
\subsection{Teaching}
An obvious application of the database is the teaching of anatomy. MyCf can be used by students to handle anatomical knwolodge within a consistent presentation. The graphical representations of anatomical entities allows a more intuitive way for knowledge-based navigation and understanding. Each anatomical entity can be displayed in 3D, while its logical relations with the other entities appear in the interface.  Varaibility can be seen as well through 3D instances saved in the database.  The Digital Anatomist Interactive Atlases integrate the FMA with 3D graphical illustrations but without real 3D interaction \cite{A-WonRosBri99}. 

\subsection{Mechanical models}
Beside geometry, we store mechanical parameters in the database, which allows to export to physical simulation engines.
The user can select the anatomical entities to be exported and the mechanical models to represent them. 
For instance, to simulate a knee, the user can decide to export the bones and the main ligaments.
Various mechanical models can be used to represent a given object, depending on the purpose of the simulation. 
For instance, studying the kinematics of a given joint based on bones and ligaments requires rigid bone models.
Alternatively, studying bone fracture requires deformable models such as finite elements.
When the rigid model is applied to a given entity, its mass and inertia matrix are automatically computed based on geometry and density.
Alternatively, the user can chose to model an entity as a Finite Element Mesh with Hooke material. 
In this case, the mass and stiffness matrices are computed automatically based on mesh geometry and shape functions as well as material parameters.

Deformable models such as finite elements require volumetric meshes.
Meshes are an important issue in simulation, and we can not propose all meshing algorithms using various complexity and quality parameters. 
When volumetric tetrahedral meshes are available in the geometric data, they can be easily exported to finite element simulation modules.
The precision and the computation time of finite element simulations heavily depend on the geometrical quality and the resolution of the volumetric meshes.
Nesme et al.'s grid-based finite elements use deformable regular grids embedding objects defined by arbitrary geometrial models~\cite{A-NesKryJerFau09}. 
The grids have arbitrary resolution, which allows to trade off accuracy for speed according to the application, and the geometrical quality is not an issue since all cells are cubes.
This approach allows to create finite element models of virtually any object at desired resolution.



\subsection{Completion of a model}
A priori knowledge is useful to complete models where not all anatomical entities are defined.
For instance, bone models may be built based on a CT-scan acquisition, whereas the connective tissues are not easily visible in the same data. In such a context, performing the mechanical simulation of a knee requires adding ligaments to the model, based on the knowledge of the ligaments and where they are attached to the bones.

MyCorporisFabrica allows the automatic creation of missing anatomical entities, using geometrical and material knowledge. The current implementation allows the creation of the main ligaments of the knee. The skeletal ligaments are modeled as one-dimensional mass-spring networks attached to the bones. To manage attach points, we have subdivided each ligamnents (using 'part of' relation) in a proximal and a distal extremities. The areas on bones where skeletal ligaments are attached are clearly defined in the ontology. We use the relation 'is inserted on' to inform where ligament's extremities are inserted. That exacte position required for a given instance should be added manualy. We're currenlty working on an automatic process to localise ligement insertions on instances using anatomical knowledge. 
Default values for spring stiffness and damping constants are stored in the database, as well as a default number of particles for the ligament. These values are modifyable by the user at creation time. Moreover, the 3D editor can be used to modify the attach points.
Figure~\ref{fig:kneemodel} illustrates this process.
\begin{figure}
\begin{center}
\begin{tabular}{cc}
 \includegraphics[height=0.3\linewidth]{genou1.png} & 
 \includegraphics[height=0.3\linewidth]{genou7.png} \\
(a) & (b)
\end{tabular}
\end{center}
\caption{Completion of a model. (a) Knee bones from an acquisition. (b) Ligament models not visible in the acquision are added using anatomical knowledge.} \label{fig:kneemodel}
\end{figure} 

Once the model is complete, it can be exported to a simulation engine, as illustrated in Figure~\ref{fig:kneesimulation}. We use the SOFA simulation library~\cite{sofa} because it handles a variety of mechanical models and their interaction, it is free, open-source and highly customizable. 
However, export plugins to other simulation engines could be easily added to MyCorporisFabrica .
\begin{figure}
\begin{center}
 \includegraphics[height=0.23\linewidth]{genou4.png}~
 \includegraphics[height=0.23\linewidth]{genou5.png}~
 \includegraphics[height=0.23\linewidth]{genou6.png}
\end{center}
\caption{Snapshots of a SOFA simulation of the model shown in Figure~\ref{fig:kneemodel}, with four ligaments. } \label{fig:kneesimulation}
\end{figure} 


\section{Discussion} \label{sec:conclusion}
To the best of our knowledge, MyCorporisFabrica is the first ....

Current limitations, future work


\bibliographystyle{plain}
\bibliography{biblio}

\end{document}
